Artificial Intelligence Engineering Manager

1 week ago

Ghaziabad, Uttar Pradesh, India beBeeGenAI Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
GenAI Engineer Job Description

We are seeking a highly skilled GenAI engineer to join our team. The ideal candidate will have a strong background in NLP, CV, and LLMs, with 5-9 years of total experience.

The successful applicant will be responsible for designing, building, fine-tuning, and deploying production-grade LLM agents and multi-modal AI applications that solve real-world business challenges.

Key Responsibilities:
  • Model & Agent Design
    • Conceptualize, design, and implement LLM-powered agents and NLP solutions tailored to business needs.
    • Build multi-agent and multi-modal AI applications/frameworks, ensuring interactivity, latency optimization, failover, and usability.
    • Apply advanced design principles for structured outputs, tool usage, speculative decoding, AST-Code RAG, streaming, and async/sync processing.
  • Hands-on Coding & Development
    • Write, test, and maintain clean, scalable, and efficient Python code for LLMs and AI agents.
    • Implement fine-tuning, embeddings, and prompt engineering with a focus on cost, latency, and accuracy.
    • Integrate models with vector databases (Milvus, Qdrant, ChromaDB, CosmosDB, MongoDB).
  • Performance & Monitoring
    • Monitor and optimize LLM agents for latency, scalability, robustness, and explainability.
    • Implement observability and guardrails strategies for enterprise-safe AI deployments.
    • Handle model drift, token consumption optimization, and error recovery mechanisms.
  • Research & Innovation
    • Read, interpret, and implement AI/Agent research papers into practical production-ready solutions.
    • Stay ahead of academic and industry trends in Agentic AI, multimodal AI, orchestration frameworks, and evaluation methodologies.
    • Experiment with new AI orchestration tools, evaluation frameworks, and observability platforms (Arize or similar).
  • Debugging & Issue Resolution
    • Diagnose and resolve model inaccuracies, system integration issues, and performance bottlenecks.
    • Apply advanced debugging techniques to troubleshoot deployment errors, data inconsistencies, and unexpected agent behaviors.
  • Continuous Learning & Adaptability
    • Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies.
    • Contribute to a culture of innovation by experimenting, prototyping, and scaling cutting-edge AI solutions.
    Required Skills & Qualifications:
    • Strong expertise in GenAI, LLMs, RAG pipelines, embeddings, and vector databases.
    • Proficiency in Python with strong debugging and system design skills.
    • Hands-on experience with Agentic AI frameworks (LangChain Agents, AutoGen, CrewAI, Temporal, DSPy).
    • Proven record of production-grade AI deployments (not just POCs).
    • Cloud experience: Azure (preferred), AWS, or GCP.
    • Knowledge of AI orchestration, evaluation, guardrails, and observability tools (Arize, Weights & Biases, etc.).

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